A general treatment of solubility 4. Description and analysis of a PCA model for ostwald solubility coefficients

Abstract

Principal component analysis (PCA) of a large data matrix (153 solvents × 396 solutes) for Ostwald solubility coefficients (log L) resulted in a two-component model covering 98.6% of the variability. Analysis of the principal components exposed the structural characteristics of solutes and solvents that codify interactions which determine the behavior of a chemical in the surrounding media. The pattern revealed by PCA analysis distinguishes solutes according to the molecular size, functional groups, and electrostatic interactions, such as polarity and hydrogen-bonding donor and acceptor properties. © 2010 American Chemical Society.